A Modification-Free Steganography Method Based on Image Information Entropy

Abstract

In order to improve the security and robustness of the Information Steganography Algorithm under strictly controlled environment, a new algorithm of modification-free steganography based on image and big data is introduced in this paper. In the proposed algorithm, a mapping relationship between the hot image entropy and the secret information is constructed and the payload information is expressed by the mapping relation. At the same time, turbo code is introduced in order to improve robustness, the hot image comes from Internet image big data, and the library of hot image is established. The performance of the proposed algorithm is analyzed using simulation experiment. Because of its none-modifying on carrier image, the results of experiment show that the proposed algorithm can achieve good performance in robustness analysis, dimension scaling attack, and rotation attack. In particular, in the test of dimension scaling attack and the rotation attack, the rate of data recovering can be over 95%. The proposed algorithm can be very valuable in the covert communication which requires high security and low volume, for example, the key exchange of symmetric encryption system.

Deep Learning Hash for Wireless Multimedia Image Content Security

“…The most essential problem of image recognition is to extract robust features. The quality of feature extraction is directly related to the effect of recognition, so most of the previous work on image recognition is spent on artificial design features [43]. In recent years, the emergence of deep learning technology has changed the status of artificial design classification characteristics.…”